What Makes RL the Hardest Workload in AI

Reinforcement learning is one of the hardest distributed systems problems in AI: training, inference, and environments all running in one loop.

Robert Nishihara, creator of Ray and co-founder of Anyscale, breaks down the anatomy of a reinforcement learning workload: the components an RL system has to coordinate, why the combination of large-scale training and large-scale inference in a single loop stresses infrastructure in ways neither does alone, and how Ray was built for exactly this shape of problem.